The present disclosure relates generally to the use of computer-based knowledge acquisition systems, and specifically to the gathering, representing, and processing of knowledge.
Artificial intelligence has long been a goal for those who design and develop computer systems. The development of such intelligence is directed toward designing systems which “think”. It is hoped that thinking systems will be able to adapt to new situations, new problems, and new forms of input. For example, one goal of artificial intelligence is to solve problems by providing previously unanticipated solutions.
Under the broad umbrella of artificial intelligence, two main approaches have developed. The first approach, known as machine learning, is directed to developing computer systems with the ability to acquire knowledge on their own from observations or through instruction. The second approach, known as knowledge acquisition, is directed to developing computer systems in which the computers are “expert” in some area. This approach includes drawing knowledge from experts, encoding this knowledge for use in a computer system, and providing software programs which use the encoded knowledge to develop solutions. Knowledge acquisition systems are generally developed using the combined effort of knowledge engineers and software engineers. The knowledge engineers and software engineers interview experts to gain knowledge, capture the knowledge, and encode the knowledge in a computer-usable format. Software may then be developed to utilize the encoded knowledge. This development process is undesirable for a number of reasons. For example, the process is often expensive, generally requires specialized training, is an inefficient use of the expert's time, and is frequently unsuccessful in producing useful knowledge or solutions.
Therefore, it is desirable to develop improved knowledge acquisition techniques and applications.